Research Projects - Climate Change (Track 1)

Climate Modeling

Climate varies across a wide range of temporal and spatial scales. The Climate Change Modeling objective is to enhance Nevada’s capability for modeling regional climate change and its effects on landscapes and ecosystems, including downscaling GCM (Global Climate Model) output.

Developing Climate Modeling will provide an infrastructure to model climate change at a regional and sub-regional scale, and assess its effects on ecosystems and resources to evaluate the effects of different future climate scenarios and adaptation strategies.

Climatic processes relevant to the complex mountainous terrain of Nevada will be better understood and modeled to become input for hydrologic, ecosystem, and wildfire models. The results will provide guidance on expected uncertainties and errors in climate predictions. These will be used to develop methods of statistical and dynamical downscaling of global climate forecasts to regional and local scales including use of principles of artificial intelligence.

Annual Report Highlights

Title: Scientists Face Challenges in Downscaling Global Climate Models

Authors: J. Mejia and D. Koracin (Desert Research Institute); K.C. King (University of Nevada, Reno/Desert Research Institute), john.mejia@dri.edu, darko.koracin@dri.edu

Nevada’s regional climate model and statistical downscaling framework that transforms relatively coarse global climate model output into finer resolutions. Bottom model layers depict downscaled data forcing a coupled surface and groundwater hydrological model developed and maintained by the USGS (Figure by John Mejia).

Outcome: Scientists at the Desert Research Institute and University of Nevada, Reno, have developed a Regional Climate Model that downscales coarse-resolution Global Climate Modeling products (~100-200 km grid size) to high-resolution spatial scales (12-36 km grid size). However, obtaining reliable estimates of the significance and uncertainty associated with downscaling present and future climate projections are persistent modeling challenges we are striving to overcome.

Impact: Regional climate data is being used to investigate regional projections of future climate for the Intermountain West, which provides valuable information to policy and decision-makers.

Additional Information: For hydrological applications, statistical, dynamical, and “hybrid” downscaling techniques are being used in forcing a coupled hydrological model in the Lake Tahoe basin, CA/NV. (Photo:Copyright 2011 Roy Tennant FreeLargePhotos.com)

This work was supported by NSF Cooperative Agreement EPS-‐0814372 to the Nevada System of Higher Education.

2009 Highlights

Presentations

Climate Modeling
Dynamical and Statistical Regional Climate Modeling	ERTAB Mtg_Koracin
Local Land Use Scenario Formulation Using IPCC SRES Climate	Regional Climate Modeling Methodological and Experimental D
Scaling Impact of Hydrologic Processes on the Integrated Res